Impacts of natural factors and farming practices on greenhouse gas emissions in the North China Plain : A meta-analysis

This work received support from the National Science and Technology Support Program (No. 2012BAD14B01), the National 948 Project (No. 2011-G30), and the Non-profit Research Foundation for Agriculture (201103039). Thanks are expressed to the anonymous reviewers for their helpful comments and suggestions that greatly improved the manuscript. The authors declare that they have no competing interests.Peer reviewedPublisher PD

A Pairwise Key Pre-Distribution Scheme for Wireless Sensor Networks

This paper, we provide a framework in which to study the security of key pre-distribution schemes, propose a new key pre-distribution scheme which substantially improves the resilience of the network compared to previous schemes, and give an in-depth analysis of our scheme in terms of network resilience and associated overhead. Our scheme exhibits a nice threshold property: when the number of compromised nodes is less than the threshold, the probability that communications between any additional nodes are compromised is close to zero. This desirable property lowers the initial payoff of smaller-scale network breaches to an adversary, and makes it necessary for the adversary to attack a large fraction of the network before it can achieve any significant gain

A Key Management Scheme for Wireless Sensor Networks Using Deployment Knowledge

To achieve security in wireless sensor networks, it is important to be able to encrypt messages sent among sensor nodes. Keys for encryption purposes must be agreed upon by communicating nodes. Due to resource constraints, achieving such key agreement in wireless sensor networks is non-trivial. Many key agreement schemes used in general networks, such as Diffie-Hellman and public-key based schemes, are not suitable for wireless sensor networks. Pre-distribution of secret keys for all pairs of nodes is not viable due to the large amount of memory used when the network size is large. Recently, a random key predistribution scheme and its improvements have been proposed

Influence of adjacent surface building on seismic response of shallow buried subway station structure

Taking the 6-storey frame structure as an example, using FLAC numerical simulation, the influence of the adjacent multi-storey buildings on the seismic response of the metro station structure (including the internal force and bias state of the station structure) is studied systematically, and the relationship between the influence and surrounding rock level change is analyzed. The research shows that the existence of surface buildings has obvious amplification effect on the internal force of the subway station and above. It mainly shows that the eccentricity of the vault of the subway station is increased, and the eccentricity of the arch waist is reduced. It has a great influence on the internal force and distribution range of the station structure. The worse the surrounding rock, the greater the internal force and influence range of the building to the station structure

Privacy-Preserving Multivariate Statistical Analysis: Linear Regression and Classification

Analysis technique that has found applications in various areas. In this paper, we study some multivariate statistical analysis methods in Secure 2-party Computation (S2C) framework illustrated by the following scenario: two parties, each having a secret data set, want to conduct the statistical analysis on their joint data, but neither party is willing to disclose its private data to the other party or any third party. The current statistical analysis techniques cannot be used directly to support this kind of computation because they require all parties to send the necessary data to a central place. In this paper, We define two Secure 2-party multivariate statistical analysis problems: Secure 2-party Multivariate Linear Regression problem and Secure 2-party Multivariate Classification problem. We have developed a practical security model, based on which we have developed a number of building blocks for solving these two problems

The prognostic value of CZT SPECT myocardial blood flow (MBF) quantification in patients with ischemia and no obstructive coronary artery disease (INOCA): a pilot study.

BACKGROUND Despite the demonstrated adverse outcome, it is difficult to early identify the risks for patients with ischemia and no obstructive coronary artery disease (INOCA). We aimed to explore the prognostic potential of CZT SPECT in INOCA patients. METHODS The study population consisted of a retrospective cohort of 118 INOCA patients, all of whom underwent CZT SPECT imaging and invasive coronary angiography (ICA). Dynamic data were reconstructed, and MBF was quantified using net retention model. Major adverse cardiovascular events (MACEs) were defined as cardiovascular death, nonfatal myocardial infarction, nonfatal stroke, heart failure, late coronary revascularization, or hospitalization for unstable angina. RESULTS During a median follow-up of 15 months (interquartile range (IQR) 11-20), 19 (16.1%) MACEs occurred; both stress myocardial blood flow (sMBF) ([Formula: see text]) and coronary flow reserve (CFR) ([Formula: see text]) were significantly lower in the MACE group. Optimal thresholds of sMBF<3.16 and CFR<2.52 were extracted from the ROC curves, and both impaired sMBF (HR: 15.08; 95% CI 2.95-77.07; [Formula: see text]) and CFR (HR: 6.51; 95% CI 1.43-29.65; [Formula: see text]) were identified as prognostic factors for MACEs. Only sMBF<3.16 (HR: 11.20; 95% CI 2.04-61.41; [Formula: see text]) remained a robust predictor when sMBF and CFR were integrated considered. Compared with CFR, sMBF provides better prognostic model discrimination and reclassification ability (C-index improvement = 0.06, [Formula: see text]; net reclassification improvement (NRI) = 0.19; integrated discrimination improvement (IDI) = 0.10). CONCLUSION The preliminary results demonstrated that quantitative analysis on CZT SPECT provides prognostic value for INOCA patients, which may allow the stratification for early prevention and intervention

A Left Ventricular Mechanical Dyssynchrony-Based Nomogram for Predicting Major Adverse Cardiac Events Risk in Patients With Ischemia and No Obstructive Coronary Artery Disease.

Background The risk stratification of patients with ischemia and no obstructive coronary artery disease (INOCA) remains suboptimal. This study aims to establish a left ventricular mechanical dyssynchrony (LVMD)-based nomogram to improve the present situation. Methods Patients with suspected coronary artery disease (CAD) were retrospectively enrolled and divided into three groups: normal (stenosis 4, summed difference score ≥2), and obstructive CAD (stenosis ≥50%). LVMD was defined by ROC analysis. INOCA group were followed up for the occurrence of major adverse cardiac events (MACEs: cardiovascular death, non-fatal myocardial infarction, revascularization, stroke, heart failure, and hospitalization for unstable angina). Nomogram was established using multivariate Cox regression analysis. Results Among 334 patients (118 [35.3%] INOCA), LVMD parameters were significantly higher in INOCA group versus normal group but they did not differ between obstructive CAD groups. In INOCA group, 27 (22.9%) MACEs occurred during a 26-month median follow-up. Proportion of LVMD was significantly higher with MACEs under both stress (63.0% vs. 22.0%, P < 0.001) and rest (51.9% vs. 20.9%, P = 0.002). Kaplan-Meier analysis revealed significantly higher rate of MACEs (stress log-rank: P = 0.002; rest log-rank: P < 0.001) in LVMD patients. Multivariate Cox regression analysis showed that stress LVMD (HR: 3.82; 95% CI: 1.30-11.20; P = 0.015) was an independent predictor of MACEs. The internal bootstrap resampling approach indicates that the C-index of nomogram was 0.80 (95% CI: 0.71-0.89) and the AUC values for 1 and 3 years of risk prediction were 0.68 (95% CI: 0.46-0.89) and 0.84 (95% CI: 0.72-0.95), respectively. Conclusion LVMD-based nomogram might provide incremental prognostic value and improve the risk stratification in INOCA patients

FT4/FT3 ratio: A novel biomarker predicts coronary microvascular dysfunction (CMD) in euthyroid INOCA patients.

Background Ischemia and no obstructive coronary artery disease (INOCA) patients who presented coronary microvascular dysfunction (CMD) demonstrate a poor prognosis, yet the risk factors for CMD remain unclear. Subtle changes in thyroid hormone levels within the normal range, especially the free thyroxine (FT4)/free triiodothyronine (FT3) ratio, have been shown to regulate the cardiovascular system. This prospective study investigated the correlation between FT4/FT3 ratio and CMD in euthyroid patients with INOCA. Methods This prospective study (www.chictr.org.cn/, ChiCTR2000037112) recruited patients with myocardial ischemia symptoms who underwent both coronary angiography (CAG) and myocardial perfusion imaging (MPI) with dynamic single-photon emission computed tomography (D-SPECT). INOCA was defined as coronary stenosis< 50% and CMD was defined as coronary flow reserve (CFR)<2.5. All patients were excluded from abnormal thyroid function and thyroid disease history. Results Among 71 INOCA patients (15 [21.1%] CMD), FT4 and FT4/FT3 ratio in CMD group were significantly higher and both showed significantly moderate correlation with CFR (r=-0.25, p=0.03; r=-0.34, p=0.003, respectively). The ROC curve revealed that FT4/FT3 ratio had the highest efficacy for predicting CMD with an optimized cutoff value>3.39 (AUC 0.78, p<0.001, sensitivity, 80.0%; specificity, 71.4%). Multivariate logistic regression showed that FT4/FT3 ratio was an independent predictor of CMD (OR 7.62, 95% CI 1.12-51.89, p=0.038, P for trend=0.006). Conclusion In euthyroid INOCA patients, increased FT4/FT3 ratio levels are associated with the occurrence of CMD, presenting a novel biomarker for improving the risk stratification